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m10-performance

Optimize Rust code performance with profiling, benchmarking, and parallelism techniques.

3|Updated Mar 22, 2026
Search Tags:#performance#optimization#profiling#cache#rust#benchmark#flamegraph
One-click install
npx skills add https://github.com/0xharryriddle/codex-field-kit --skill m10-performance-0xharryriddle
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: m10-performance
Source: https://github.com/0xharryriddle/codex-field-kit/tree/main/archive/upstream/chasebuild-agent-skills/rust/skills/m10-performance
Command: npx skills add https://github.com/0xharryriddle/codex-field-kit --skill m10-performance-0xharryriddle

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides structured guidance to optimize Rust code performance, helping teams identify bottlenecks, choose effective strategies, and implement fast, reliable improvements.

Core Features & Use Cases

  • Performance-focused guidance for Rust projects, including profiling, benchmarking, and optimization patterns.
  • Techniques for memory layout, allocation reduction, and parallelism to achieve measurable speedups.
  • Use Case: a Rust service that experiences high latency can apply these practices to reduce hot paths and improve throughput.

Quick Start

Run a benchmark to identify bottlenecks and apply proven Rust optimization techniques.

Frequently Asked Questions about m10-performance

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I profile Rust performance bottlenecks using flamegraphs?▼

Profile Rust performance by generating flamegraphs to identify hot paths and CPU bottlenecks. This technique reveals exact function call frequencies to pinpoint where code-level optimizations are needed most.

What's the best way to reduce memory allocations in Rust?▼

Reduce Rust memory allocations using preallocation and cache-friendly data layouts. These optimization patterns minimize allocation overhead and improve cache locality for measurable speedups.

Can I use Rayon for parallelism to speed up my Rust service?▼

Rayon-based parallelism is supported to accelerate Rust performance. It enables data parallelism across collections, improving throughput for computationally intensive tasks without altering core logic.

How do I benchmark Rust code with Criterion?▼

Benchmark Rust code with Criterion to measure execution time and detect regressions. Running benchmarks identifies bottlenecks and validates that applied optimizations yield measurable speedups.

Does Rust performance optimization work for libraries and crates?▼

Rust performance optimization applies to both crates and libraries. Techniques like preallocation, cache-friendly layouts, and profiling can be integrated across dependencies to reduce latency.

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